Project description:The role and mechanism of CSTF2 in hepatocellular carcinoma are unclear. We constructed CSTF2 knockout HUH7 and PLC/PRF/5 cells to analyze the function of CSTF2 in liver cancer and the downstream gene changes it induces.
Project description:CSTF2, an RNA-binding protein, and its target genes in hepatocellular carcinoma remain unreported. Screening for potential CSTF2-bound RNA sequences was performed using RIP-seq technique in HUH7 cells.
Project description:CSTF2 has been shown to have a certain oncogenic effect in hepatocellular carcinoma, but its mechanism remains unclear. Previous studies have suggested that CSTF2 can shorten the 3' untranslated region (3'UTR) of target genes. Considering that the 3'UTR contains numerous m6A modification sites, we hypothesize that CSTF2 may regulate mRNA m6A modification. We performed MeRIP-seq analysis to investigate the changes in m6A modification in CSTF2 knockout HUH7 and PLC/PRF/5 cell lines.
Project description:Recent studies have shown that high cell cycle activity negatively correlates with antitumor immunity in certain cancer types. However, a similar correlation has not been proven in liver cancer.We downloaded transcriptomic profiles of TCGA-LIHC (the cancer genome atlas-liver hepatocellular carcinoma) and assessed the cell cycle distribution of samples using single sample gene set enrichment analysis (ssGSEA), termed the cell cycle score (CCS). We obtained cell cycle-related differentially expressed prognostic genes and identified CENPA, CDC20 and CTSV using LASSO regression. We studied the effect of CTSV on clinical features and immune alterations in liver cancer based on TCGA-LIHC data. In vitro and in vivo experiments were performed to validate the role of CTSV in liver cancer using liver cancer cell lines and tissues.We found that the CCS closely correlated with the clinical features and prognosis of patients in TCGA-LIHC. Analysis of differentially expressed genes (DEGs), univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression identified cathepsin V (CTSV) with prognostic significance in LIHC. Importantly, single-gene survival analysis of CTSV using microarray and sequencing data indicated that high levels of CTSV expression correlated with an unfavorable prognosis in various cancers. Gene set enrichment analysis (GSEA) revealed that high CTSV expression closely correlated with decreased expression of metabolic genes and increased expression of cell cycle genes. Furthermore, difference and correlation analyses of the relationship between CTSV expression and immune infiltrates, determined using CIBERSORT and TIMER algorithms, revealed that CTSV expression correlated with macrophages and CD4+ T cells. In vitro and in vivo experiments revealed that knockdown of CTSV inhibited liver cancer cells proliferation. Immunohistochemical staining showed that high CTSV expression correlated with macrophage infiltration in liver cancer tissues, predicted a poor prognosis, and may serve as a biomarker for HCC therapy.In conclusion, CTSV is a novel cell cycle prognostic gene that can affect HCC cells proliferation, and a potential biomarker for HCC therapy.
Project description:The aim of this study was to screen abnormal lncRNAs in the progression of hepatocellular carcinoma through high-throughput sequencing, and to screen the biomarkers for prognosis and diagnosis of hepatocellular carcinoma. Transcriptome analysis of 6 samples was completed in this project. A total of 93.581 Gb Clean Data (sequencing Data after quality control) was obtained. The average amount of Clean Data of each sample was 15.597 Gb. The Q30 base percentage was above 93.69 % and GC content was between 44.95% and 50.05%. In conclusion, sequencing analysis provided a landscape for abnormal regulation of lncRNAs, and screened out a significantly different lncRNAs ZFAS1. ZFAS1were found to be overexpressed in hepatocellular carcinoma tissues and correlated with malignant status and prognosis of hepatocellular carcinoma patients, and ZFAS1 silencing inhibited proliferation, migration and invasion of SK-Hep1 cells. The overexpression of miR-582-3p can eliminate the inhibitory effect of ZFAS1 silencing on SK-Hep1 cells, which may be valuable for the diagnosis and treatment of hepatocellular carcinoma. ZFAS1 may be a new potential biomarker for liver cancer. Further studies on the regulatory process of ZFAS1/miR-582-3p will help us to understand the mechanism of the occurrence and development of liver cancer
Project description:BackgroundThe shortening of 3' untranslated regions (3'UTRs) of messenger RNAs(mRNAs) by alternative polyadenylation (APA) is an important mechanism for oncogene activation. Cleavage stimulation factor 2 (CSTF2), an important regulator of APA, has been reported to have a tumorigenic function in urothelial carcinoma of the bladder and lung cancers. However, the tumor-promoting role of CSTF2 in hepatocellular carcinoma (HCC) and its underlying molecular mechanism remains unclear.MethodsMultiple databases were used to analyze the expression level and prognostic value of CSTF2 in HCC. Function enrichment analysis was used to investigate the molecular mechanism of CSTF2 for the occurrence and development of HCC. The biological function in HCC cell lines in vitro was determined by CCK8, colony formation, Transwell migration, and invasion assay. Moreover, the tumorigenic function of CSTF2 in vivo was measured by a subcutaneous tumor formation or injecting four plasmids into a mouse tail vein within 5-7 s in an immunocompetent HCC mouse model. In addition, aerobic glycolysis in HCC cells was determined by measuring the extracellular acid rate (ECAR) and extracellular glucose and lactate levels.ResultsBioinformatics analysis revealed that CSTF2 was overexpressed in HCC tissues. The high expression of CSTF2 was correlated with a poor prognosis and high histological grades. CSTF2 knockout inhibited the proliferation, migration, and invasion of HCC cells. In addition, CSTF2 knockout HCC cells failed to form tumors by a subcutaneous graft experiment. Furthermore, endogenous CSTF2 knockout attenuated hepatocarcinogenesis in an immunocompetent HCC mouse model. Function enrichment analysis suggested that the high expression of CSTF2 was associated with enhanced glycolysis. Moreover, we found that CSTF2 knockout reduced the level of the short 3' UTR isoform of hexokinase 2 and increased its level of long 3'UTR. Furthermore, CSTF2 knockout inhibited ECAR levels, glucose uptake, and lactate production.ConclusionOur results indicated that CSTF2 is highly expressed in HCC and is correlated with a poor prognosis and high histological grade. The knockout of CSTF2 inhibits the tumorigenesis and procession of HCC both in vitro and in vivo. Moreover, CSTF2 is associated with enhanced glycolysis. Therefore, this study suggests that CSTF2 might be a new prognostic biomarker and therapeutic target for HCC.
Project description:An integrative transcriptomics analysis was performed to evaluate the clinical relevance of genes associated with hepatocyte differentiation in human hepatocellular carcinoma (HCC). The well-established HepaRG cell line model was used to define a gene expression signature reflecting the status of tumor hepatocyte differentiation. This signature was able to stratify HCC patients into clinically relevant molecular subtypes. Then, a minimal subset of 7 differentiation-associated genes was identified to predict a poor prognosis in several cancer datasets. Hepatocellular carcinoma (HCC) is a deadly cancer worldwide as a result of a frequent late diagnosis which limits the therapeutic options. Tumor progression is correlated with a dedifferentiation of hepatocytes, the main parenchymal cells in the liver. Here, we hypothesized that the level of expression of genes reflecting the differentiation status of tumor hepatocytes could be clinically relevant in defining subsets of patients with variable clinical outcomes. To test this hypothesis, an integrative transcriptomic approach was used to stratify a cohort of 139 HCC patients based on a gene expression signature established using a well-controlled in vitro model of tumor hepatocyte differentiation in HepaRG cell line. First, we validated the HepaRG model by identifying a robust gene expression signature associated with hepatocyte differentiation and liver metabolism. This signature was able to distinguish specific developmental stages in mice. More importantly, the signature identified a subset of human HCC associated with a poor prognosis and cancer stem cell features. By using an independent HCC dataset (TCGA), a minimal subset of 7 differentiation-related genes was shown to predict a reduced overall survival, not only in patients with HCC but also in other types of cancers (e.g. kidney, pancreas, skin). In conclusion, the study demonstrates that genes reflecting the differentiation status of tumor hepatocytes are clinically relevant for predicting the prognosis of HCC patients.